ScaleOps Reviews & Product Details

I love how ScaleOps provides a seamless setup process, which is as simple as deploying any other Kubernetes workload, making it extremely user-friendly. The dashboard is incredibly useful, offering automation with a single click and providing valuable suggestions tailored to my workload, such as predicting optimal resource percentages. ScaleOps solves the significant problem of resource optimization by automatically adjusting memory and CPU utilization based on traffic and usage, which has led to a substantial cost savings of 30 to 40% in my infrastructure costs. I appreciate the core VPA scaling feature that efficiently adjusts resources to traffic patterns, ensuring both performance and cost-efficiency. I also enjoy the troubleshooting features that offer out-of-the-box insights on issues like memory or pod capacity, which is a considerable time-saver compared to using tools like Grafana. Additionally, I highly value their incredible team and great support, an aspect that contributes significantly to my satisfaction, resulting in a perfect recommendation score from me. Review collected by and hosted on G2.com.

I think ScaleOps could enhance their horizontal pod autoscaling (HPA) feature and explore its functionalities further. Additionally, I am in discussions with them about introducing daemon set scaling based on node size, which is a feature I believe would be extremely beneficial. Review collected by and hosted on G2.com.

ScaleOps was easy to setup in our 6 main GKE clusters each with about ~1k unique workloads using 350 nodes and ~3k cores in total. We worked closely with ScaleOps' team during the integration, and they provided support quickly. We've saved about 30k USD per month in compute costs with ScaleOps optimized rightsizing since installing it. In addition to cost savings, we've seen a huge improvement in the frequency of OOM kills in the platform, from The automated right-sizing is much easier to scale in our organization with hundreds of developers than previous solutions for workload right-sizing. The custom policies of ScaleOps make it easy to control right-sizing for different workloads' latency, reliability, and technical needs, giving us the flexibility to drive aggressive cost optimization where we can, while leaving a wide berth for more critical and demanding workloads. Using their GitOps-style configuration of policies and attaching workloads to those policies allows us to control this at scale despite having 6k distinct workloads to configure. Review collected by and hosted on G2.com.

While running ScaleOps in-cluster offers certain benefits for reliability and security, the required Prometheus deployment consumes a significant amount of CPU and memory, which reduces our overall cost savings. Additionally, managing Prometheus ourselves means we need to develop expertise in its operation to keep ScaleOps functioning properly. As with automated rightsizing, relying on ScaleOps to maintain optimal workload sizing introduces a dependency, making ScaleOps itself a potential single point of failure in our infrastructure. There are also some bugs in the UI. For example, CronJobs do not apply their GitOps-configured policies until they actually run. The user interface is extremely sluggish, likely because of the high number of workloads we have. It appears the front-end loads all workloads into memory and manipulates them during interaction, which causes slow JavaScript responses to actions like clicking and mouse-over.

Many of the features besides workload rightsizing seem immature and/or don't provide anything more than what is provided baseline by Kubernetes or GKE. For example the cluster headroom can easily be accomplished using the official Kubernetes node over-provisioning documentation (https://kubernetes.io/docs/tasks/administer-cluster/node-overprovisioning/) with significantly more ability to customize for your use-case. Their "spot optimization" feature doesn't provide any value-add for us that we don't already get from GKEs built-in compute-class feature. I'm not sure of the real-world use-case of their replicas optimization feature, but it seems completely useless to us. I think the other features besides workload rightsizing have been added as fluff to market the product to management without providing real-technical value to companies using ScaleOps. This isn't a real a problem for us, as we weren't interested in anything but workload rightsizing when we purchased the solution. Review collected by and hosted on G2.com.

I like that as a company, ScaleOps has been very easy to work with and they've been flexible on pricing. They've provided really good support overall. The product itself is very slick and easy to use, and it's done what it's advertised and more. Review collected by and hosted on G2.com.

We had a little bit of difficulty getting it initially set up and communicating to our internal teams about the benefits of ScaleOps and why it's worth the operational cost. Review collected by and hosted on G2.com.

While I greatly appreciate the cost savings aspect of ScaleOps, I find it as one of my go-to tools for general observability/monitoring of our system. It provides me with an easy way to see potential issues and misconfigurations within our system. We have unearthed many "skeletons" from ScaleOps. Finally, I would be remiss without calling out the support from the ScaleOps team. On multiple occasions, we had issues in the system and the ScaleOps team helped us analyze and remediate. The issue was NOT caused by ScaleOps tooling, but they were patient and dedicated enough to walk us through the real root cause. Review collected by and hosted on G2.com.

I wouldn't call it a dislike, but I would like to see continued feature enrichment on the node management and host side. I can see what ScaleOps wants to do, but I have a difficult time following Karpenter's decision making. I would like to see this in a fully integrated view to understand pod and node movement. Additionally, I have specialized nodes running their own host applications, outside the purview of Kubernetes and sometimes impacting resource management. It would be incredible to have ScaleOps be aware of those system resource usage and factor that into kubelet/system reserved capacity. Review collected by and hosted on G2.com.

As an administrator, my experience with ScaleOps has been highly positive. The platform stands out for its ease of deployment and management, allowing quick onboarding and seamless integration with existing Kubernetes environments. The setup process is intuitive, requiring minimal manual configuration while still offering full control for advanced users.

From a cost optimization perspective, ScaleOps delivers measurable results. Its intelligent automation dynamically adjusts resources based on workload demand, helping to significantly reduce infrastructure costs without compromising performance or stability. The built-in monitoring and analytics tools provide clear visibility into cluster utilization and scaling behavior, simplifying both operations and troubleshooting.

ScaleOps also offers granular configuration options, enabling precise fine-tuning of scaling policies. Administrators can easily tailor thresholds, scaling intervals, and node group behaviors to align with application-specific needs or business SLAs. This flexibility ensures an optimal balance between performance and cost efficiency.

Another strong point is the responsiveness and support quality from the ScaleOps team. Both the customer support and development teams have been proactive, providing timely assistance, clear documentation, and incorporating feedback into product updates. Their engagement reflects a genuine commitment to continuous improvement and customer success.

Overall, ScaleOps is a robust, cost-effective, and admin-friendly automation platform that enhances operational efficiency, reduces cloud spend, and empowers teams to focus more on innovation rather than infrastructure management. Review collected by and hosted on G2.com.

The platform lacks sufficient fault-tolerance in its automation workflows. It’s possible to accidentally trigger a cluster automation without any confirmation or rollback option. There’s no secondary protection step or abort mechanism, which increases the risk of unintended actions on live clusters.

Additionally, the update and versioning approach is not very straightforward. Bug fixes are released under the same version tag, which can create confusion when tracking system updates or validating compatibility across environments. A clearer versioning policy and more transparent update process would help improve operational control and confidence. Review collected by and hosted on G2.com.

I find ScaleOps incredibly effective for automating resource optimization across our Kubernetes clusters, which has significantly improved our cost efficiency and reduced the need for manual intervention. The ease of use and intuitive, clear UI make navigating and applying different policies straightforward, especially with the helpful auto-detection feature. ScaleOps' proactive support is remarkable; they initiate contact when issues arise, providing guidance and hands-on help without us needing to reach out first. I also appreciate the feature that displays resource utilization for each node, providing clear visibility into cluster performance, which, along with the ability to compare memory and CPU requests versus actual usage over time, aids us in understanding and optimizing resource efficiency. These capabilities help us make informed decisions about scaling and resource allocation, preventing over-provisioning and improving operational efficiency. I particularly admire the ease of setup and the support we received, which clarified limitations and helped address any challenges effectively. Overall, ScaleOps is a reliable tool that I'd choose again for its user-friendly interface, proactive support, and efficient resource optimization capabilities, and I would highly recommend it. Review collected by and hosted on G2.com.

I experienced situations where the cluster didn't have enough available resources due to additional replicas attempting to scale up without finding a free node. Also, there were instances where replicas did not initially receive the ScaleOps resource definitions, disrupting their operations. Furthermore, we faced cases where a resource would not immediately adopt the ScaleOps configurations, requiring termination or a restart before the proper policy was applied. Review collected by and hosted on G2.com.

While Kubernetes now supports native vertical pod autoscaling, it's very helpful to have a proper UI with dashboards and being able to search through the entire workloads.

The built-in policies works perfect for most of the cases.

The error and warning indicators in "Node Management" and "Pods Rightsizing" help us to find infrastructure issues. Review collected by and hosted on G2.com.

It gets really slow when working against large EKS cluster (800 Nodes).

When aggregation 10+ clusters, indexing also get slow.

Would love more examples or clearer descriptions on configurable parameters in policies, etc. Review collected by and hosted on G2.com.

ScaleOps has been a game changer for managing our cloud resources efficiently. The platform provides clear visibility into cluster performance and resource utilization, helping us optimize workloads automatically without constant manual intervention. I especially appreciate how seamless it is and how intuitive the UI is — you can immediately see where savings are coming from. The automation features around scaling and right-sizing save both time and cost, and the reporting insights make it easy to communicate value to stakeholders. Overall, it simplifies complex cloud optimization into something actionable and easy to manage. Review collected by and hosted on G2.com.

There’s very little to dislike. Occasionally, the recommendations can take a bit of time to refresh after major configuration changes. Review collected by and hosted on G2.com.

ScaleOps offers a transparent and automated layer of intelligence for optimizing Kubernetes clusters. What I appreciate most is the level of transparency and control it provides; unlike black-box autoscalers, ScaleOps allows me to see the reasoning behind every recommendation or adjustment it makes. The insights into cluster utilization and potential savings are outstanding, and its integration with our existing CI/CD and monitoring workflows has been completely seamless.

Most importantly, their customer support is exceptional; They are very responsive, knowledgeable, and genuinely considerate. It’s one of the best support experiences I’ve encountered. Review collected by and hosted on G2.com.

There are a lot of upgrades, which can feel excessive at times. However, I understand that since Kubernetes is updated frequently and its features evolve, the developers need to continually adjust the code to keep up. Review collected by and hosted on G2.com.

It does what it needs to be done - it saves money :)

It also nice to have the dashboards and monitoring tools even though its not what it meant to be from my point of view.

We use if in a few "low" environment and didn't face any major issues.

Once implemented, its really easy to use and control. Review collected by and hosted on G2.com.

We had some performance issues while using Scaleops in our production environment causing us to partly disabling it and losing trust in the product.

The configuration can be easier to control. Review collected by and hosted on G2.com.